Field of the Invention (Technical Field)
Embodiments of the present invention relate to predicting dollar cost estimates based on related predictor variables obtained from one or more data sources. The dollar cost estimates provide a more accurate and reliable figure of the actual dollar cost of the entities to which they pertain.
Description of Related Art
Consumers often use the internet to research the dollar cost of entities, such as restaurants, hotels, attractions, or services, to aid in choosing a specific entity to visit or purchase. They may do so on websites that host information about entities of interest. For example, someone seeking the dollar cost of local restaurants may use a site like Zagats.com or Yelp.com. The dollar cost provided by such sites is usually a fixed cost for a particular selection of services or products. For instance, a website like Orbitz.com might post the average dollar cost of a nightly stay at a particular hotel. Different sites may post different dollar costs for the same entity based on differing criteria for determining cost, which may cause consumer confusion when trying to choose a particular entity. The data on dollar cost available to a consumer may be missing, inaccurate, or only an approximation. This is in contrast to cost information concerning items directly for sale on a website or in a store, where every item will generally have a clearly defined dollar cost, and those that do not will essentially be unavailable for purchase.
In addition to entities' dollar costs, websites often provide a host of other information pertaining to entities of interest. A site like Zagats.com or Yelp.com, for instance, might provide information like ratings of restaurants' food quality, the location of restaurants, the dress code, or even symbolic information about cost like a set of increasing dollar signs ($, $$, $$$, $$$$). Consumers often attempt to evaluate and choose entities based on the dollar cost and other information provided by such websites with no means of measuring the quantitative relationship between different types of information and dollar cost. There may be, however, a mathematical relationship between dollar cost and other information. For example higher ratings and better locations may both correlate to higher dollar costs for a group of restaurants, but the human mind is unable to calculate those relationships and apply them to select the entity with the best value for the money. This is especially true when there is a large number or entities to choose from. The consumer ends up choosing on gut instinct and may not be pleased with the end result.
Consumers would benefit from a means for consolidating information about entities from one or more websites and mathematically correlating as much information as possible to the fixed dollar costs of the entities to generate an adjusted, more realistic estimate of the price of the restaurant. Similarly, when dollar cost is unavailable, consumers may benefit from a statistically determined dollar cost based on other available information about the entities. Specifically, calculating a cost in dollars for entities based on statistically modeling the relationships between dollar costs and other information would provide a useful mechanism for distinguishing between the true price of entities. For example, modeling the relationship between the costs of restaurants to, for example, their location and dress code can form the basis for calculating adjusted dollar cost figures. Consumers could then quantitatively compare a single adjusted dollar cost figure to the dollar costs available from various data sources for each entity, thereby providing a simple mechanism for gauging the true value of entities based on all available information. Accordingly, there is a need for methods to statistically model adjusted dollar cost for entities based on the relationships between cost and other information.